transpose¶

paddle. transpose ( x, perm, name=None ) [源代码] ¶

该OP根据perm对输入的多维Tensor进行数据重排。返回多维Tensor的第i维对应输入Tensor的perm[i]维。

参数：

x (Tensor) - 输入：x:[N_1, N_2, ..., N_k, D]多维Tensor，可选的数据类型为float16, float32, float64, int32, int64。
perm (list|tuple) - perm长度必须和X的维度相同，并依照perm中数据进行重排。
name (str) - 该层名称（可选）。

返回：多维Tensor

返回类型：Tensor

示例:

x = [[[ 1  2  3  4] [ 5  6  7  8] [ 9 10 11 12]]
    [[13 14 15 16] [17 18 19 20] [21 22 23 24]]]
shape(x) =  [2,3,4]

# 例0
perm0 = [1,0,2]
y_perm0 = [[[ 1  2  3  4] [13 14 15 16]]
          [[ 5  6  7  8]  [17 18 19 20]]
          [[ 9 10 11 12]  [21 22 23 24]]]
shape(y_perm0) = [3,2,4]

# 例1
perm1 = [2,1,0]
y_perm1 = [[[ 1 13] [ 5 17] [ 9 21]]
          [[ 2 14] [ 6 18] [10 22]]
          [[ 3 15]  [ 7 19]  [11 23]]
          [[ 4 16]  [ 8 20]  [12 24]]]
shape(y_perm1) = [4,3,2]

代码示例:

import paddle

x = paddle.randn([2, 3, 4])
x_transposed = paddle.transpose(x, perm=[1, 0, 2])
print(x_transposed.shape)
# [3L, 2L, 4L]

PaddlePaddle

paddle / transpose

transpose¶

PaddlePaddle

paddle

paddle.amp

paddle.callbacks

paddle.compat

paddle.distributed

paddle.distribution

paddle.fluid

paddle.io

paddle.jit

paddle.metric

paddle.nn

paddle.onnx

paddle.optimizer

paddle.regularizer

paddle.static

paddle.sysconfig

paddle.text

paddle.utils

paddle.vision

paddle / transpose

transpose¶